%0 Generic
%A Bloemendaal, Nadia
%A de Moel, H. (Hans)
%A Martinez, Andrew B.
%A Muis, S. (Sanne)
%A Haigh, I.D. (Ivan)
%A van der Wiel, Karin
%A Haarsma, R.J. (Reindert)
%A Ward, P.J. (Philip)
%A Roberts, Malcolm
%A Dullaart, Job
%D 2023
%T STORM Climate Change synthetic tropical cyclone tracks
%U 
%R 10.4121/14237678.v2
%K Natural hazards
%K Statistical Modelling
%K Tropical Cyclones
%K Synthetic Tropical Cyclone geneRation Model (STORM)
%K Synthetic modelling
%K Synthetic tracks
%K dissertation
%K International Best Track Archive for Climate Stewardship (IBTrACS)
%K HighResMIP
%K PRIMAVERA
%X <p>UPDATE 22/06/2023: Tom Russell (Oxford University) and colleagues have created global .tiff maps for the return period datasets. You can find them here: <a href="https://zenodo.org/record/7438145" target="_blank">https://zenodo.org/record/7438145</a></p><p><br></p><p>Datasets consisting of 10,000 years of synthetic tropical cyclone tracks, generated using the Synthetic Tropical cyclOne geneRation Model (STORM) algorithm (see Bloemendaal et al (2020)). The dataset is generated by extracting the climate change signal from each of the four general circulation models listed below, and adding this signal to the historical data from IBTrACS. This new dataset is then used as input for STORM, and resembles future-climate (2015-2050; RCP8.5/SSP5) conditions. The data can be used to calculate tropical cyclone risk in all (coastal) regions prone to tropical cyclones.</p><p><br></p><p>Climate change information from the following models is used in this study (each model has its own 10.000 years of STORM data):</p><p>1) CMCC-CM2-VHR4</p><p>2) CNRM-CM6-1-HR</p><p>3) EC-Earth3P-HR</p><p>4) HAdGEM3-GC31-HM</p><p><br></p><p>See Roberts et al (2020) for more information on these models.</p>
%I 4TU.ResearchData